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October 8, 20250 citationsOpen Access

Human-In-The-Loop Software Development Agents: Challenges and Future Directions

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JPJirat PasuksmitThe University of MelbourneWTWannita TakerngsaksiriMonash UniversityPTPatanamon ThongtanunamThe University of Melbourne

Key Points

  • The study reveals significant challenges in evaluating human-in-the-loop software development systems, especially regarding costs.
  • Key metrics highlight high computational costs of unit testing and variability in LLM-based evaluations of code quality.
  • Assessment involved human-in-the-loop software agents deployed to resolve work items, leveraging LLMs for code generation.
  • Future research is essential to enhance evaluation frameworks for human-in-the-loop software development tools.

Abstract

Multi-agent LLM-driven systems for software development are rapidly gaining traction, offering new opportunities to enhance productivity. At Atlassian, we deployed Human-in-the-Loop Software Development Agents to resolve Jira work items and evaluated the generated code quality using functional correctness testing and GPT-based similarity scoring. This paper highlights two major challenges: the high computational costs of unit testing and the variability in LLM-based evaluations. We also propose future research directions to improve evaluation frameworks for Human-In-The-Loop software development tools.

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Cite This Study

Pasuksmit et al. (2025) studied this question.

synapsesocial.com/papers/68e5c1c76950a706b22b5de6https://doi.org/10.48550/arxiv.2506.11009
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